Summary
MOB samenvatting stappen in R en rapportage
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MOB samenvatting stappen in R en rapportage Behaald resultaat: 19/20
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By: tinnevanboxel • 2 year ago
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Samenvatting werken in R MOBKolommen en rijen selecteren
Data_a<-Data[c(1:10), c(1:20)]
o Voor komma rijen, na komma kolommen
o Leeglaten = alle rijen/kolommen
Rijen kolom selecteren adhv variabele
o Data_a<-Data[which(Data$V1==”naam1” | Data$V1==”naam2”), ]
NA’s verwijderen
Data_compleet<-Data[complete.cases(Data), ]
Data samenvoegen
Data<-rbind(Data_a, Data_b)
Data<-data.frame(D$V1, D$V2, D$V3)
1
, H2: Observeren
Interbeoordelaarsbetrouwbaarheid nagaan
Categorische variabele Variabele van interval – of
ratio niveau
2 beoordelaars Cohen’s Kappa ICC
Meer dan 2 beoordelaars Fleiss Kappa ICC
Cohen's Kappa
categorisch, 2 beoordelaars
Soms heeft dataset ook randinformatie -> nieuw object aanmaken met enkel variabelen die
observaties bevatten
pakket: library(irr)
Functie: kappa2(Data1)
Stappen
o Dataset aanmaken
OnderzoekerA <- c("A", "A", "A", "A", "B", "B", "B", "A", "B", "B")
OnderzoekerB <- c("A", "A", "A", "A", "B", "B", "B", "B", "A", "A")
Data1 <- data.frame(OnderzoekerA, OnderzoekerB)
Data1
o Cohen’s Kappa berekenen
library(irr)
kappa2(Data1)
Interpretatie
o Vuistregel Landis & Koches
o De Cohen’s kappa bedraagt… . Met betrekking tot de
interbeoordelaarsbetrouwbaarheid kunnen we stellen dat er weinig tot
geen/beperkte/matige/sterke/zeer sterkte tot volledige overeenkomst is tussen de
beoordelaars.
Fleiss' Kappa
categorisch, > 2 beoordelaars
pakket: library(irr)
Functie: kappam.fleiss(Data1)
o gedetailleerd per coderingsstrategie: kappam.fleiss(Data1, detail=TRUE)
Stappen
o dataset aanmaken
2
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